Sparse plus low-rank identification for dynamical latent-variable graphical AR models

Cites Work

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Sparse inverse covariance estimation with the graphical lasso
Latent variable graphical model selection via convex optimization
Combined parameter and output estimation of dual-rate systems using an auxiliary model
Schur complements and statistics
Generalized maximum entropy based identification of graphical ARMA models
Empirical Bayesian learning in AR graphical models
Exact matrix completion via convex optimization
Large dynamic covariance matrix estimation with an application to portfolio allocation: a semiparametric reproducing kernel Hilbert space approach
AR Identification of Latent-Variable Graphical Models
Rank-Sparsity Incoherence for Matrix Decomposition
Modelling multiple time series via common factors
High-Dimensional Statistics
A Scalable Strategy for the Identification of Latent-Variable Graphical Models
High-Dimensional Data Analysis with Low-Dimensional Models
Factor Models With Real Data: A Robust Estimation of the Number of Factors
A Maximum Entropy Solution of the Covariance Extension Problem for Reciprocal Processes
ARMA Identification of Graphical Models
The Circulant Rational Covariance Extension Problem: The Complete Solution
Learning Latent Variable Dynamic Graphical Models by Confidence Sets Selection
Graphical interaction models for multivariate time series.
Data-Driven Link Prediction Over Graphical Models
A multi-period constrained multi-objective evolutionary algorithm with orthogonal learning for solving the complex carbon neutral stock portfolio optimization model
Topology Learning of Linear Dynamical Systems With Latent Nodes Using Matrix Decomposition

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